silence HantushWellModel info msg about r=1.0

[dbrakenhoff]

This PR silences the info message internally by adding a warn keyword argument and checking whether the current rfunc is HantushWellModel in ps.Model methods.

In my opinion this is a bit ugly, but perhaps worth silencing the confusing message? So far 3 issues have been posted about it, so it is confusing people.

Checklist before PR can be merged:

• closes issue Issues with WellModel [BUG] #602
• is documented
• Format code with Black formatting
• type hints for functions and methods
• tests added / passed
• Example Notebook (for new features)
• Remove output for all notebooks with changes

[codacy-production]

Coverage summary from Codacy

Merging #604 (e769550) into dev (f8b0771) - See PR on Codacy

Coverage variation	Diff coverage
❌ -0.05% (target: +0.00%)	70.97%

Coverage variation details

	Coverable lines	Covered lines	Coverage
Common ancestor commit (f8b0771)	4955	3599	72.63%
Head commit (e769550)	4976 (+21)	3612 (+13)	72.59% (-0.05%)

Coverage variation is the difference between the coverage for the head and common ancestor commits of the pull request branch: <coverage of head commit> - <coverage of common ancestor commit>

Diff coverage details

	Coverable lines	Covered lines	Diff coverage
Pull request (#604)	31	22	70.97%

Diff coverage is the percentage of lines that are covered by tests out of the coverable lines that the pull request added or modified: <covered lines added or modified>/<coverable lines added or modified> * 100%

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[raoulcollenteur]

@dbrakenhoff , thanks for the PR. I see that fixing this would be nice.

I thought of another (easyier?) fix. Can we not deal with the distance=None issue when creating a WellModel instance? An assign r=1 if no distances are provided? That would fix it as well write? It seems to me that r should not be None in all cases anyway.

Cheers,
Raoul

[dbrakenhoff]

That could work, and we could set the default value to 1 m or the distance to the first well. But that would mean users would have to be aware that when using ml.<method> some assumption is being made about which distance is used. I'm not sure if a silent assumption is the way to go here.

I think my preference is this PR, which provides a warning when users call ml.<method> on WellModels directly, but otherwise stays silent. But I'm open to others opinions/votes on this issue :).

[raoulcollenteur]

I agree that it's better to make there users aware and raise a warning. Still, could we not do that when creating the stress model without a distance and setting r to 1, and raising the warning once upon creation? Would prevent a lot of code and it would not be a silent assumption right?

[dbrakenhoff]

I agree that it's better to make there users aware and raise a warning. Still, could we not do that when creating the stress model without a distance and setting r to 1, and raising the warning once upon creation? Would prevent a lot of code and it would not be a silent assumption right?

The trouble is that the warning isn't likely to be generated at creation, but when users want to use the Model class convenience methods for getting information from the stressmodels (i.e. ml.get_step_response). So for now, I think this is the best solution, even though it does add some extra code.